Method and apparatus for estimating temperature in a body

ABSTRACT

The invention relates a method and an apparatus of predicting or planning a temperature distribution ( 52 ) in a body. The method comprises the steps of : a) obtaining a model of the body ( 50 ) related to a temperature transport mechanism or temperature distribution ( 52 ) in the body; b) simulating an application of heat to at least a part of the body such as targeted tissue; c) determining and/or predicting the temperature ( 52 ) or heat distribution in at least a part of the body using the model of the body ( 50 ).

FIELD OF THE INVENTION

The present invention relates to a method and to an apparatus forestimating a temperature distribution in a body such as a biologictissue or lifeless material.

BACKGROUND OF THE INVENTION

The problem of temperature measurement in a body, such as biologic orliving tissue, generally goes with an invasive process. However, theintroduction of a foreign body into the tissue leads to obviousinconveniences. Until now, several physical processes have beenconsidered with the aim of solving this problem.

Microwave radiometry for example appears to be well suited fortemperature investigations of moderately deep-seated tissues. However, amajor drawback of this process is related to the noise power emitted bya lossy material, which limits the depth of tissues under investigation.

In active ultrasound methods, a search for appropriate parameters fortemperature sensing is a very difficult task. Ultrasound speed in tissuevaries with temperature because the density of the tissue varies withtemperature. However, the density varies also due to temperatureindependent tissue properties such as fat or water content,multipath-scattering and multiple reflections.

SUMMARY OF THE INVENTION

It is an object of the invention to provide a reliable method andapparatus for predicting or calculating the temperature in a body, suchas for example biologic tissue.

This object is solved by the method and the apparatus as defined in theindependent claims. Preferred embodiments are defined in the dependentclaims.

According to an aspect of the invention, a method of predicting orplanning a temperature distribution in a biologic tissue such as a bodyis suggested. The temperature distribution is related to the space andtime dependency of the temperature. The space dependency may concern thevariation of temperature inside the body as a function of position. Thetime dependency may concern the variation of temperature as a functionof time. The temperature may refer to an absolute value of thetemperature, as well as to a relative value indicating a temperaturevalue at a first position and/or first time as being higher or lowerthan or equal to a temperature value at a second position and/or secondtime.

Predicting a temperature distribution may refer to determining,calculating or obtaining the value distribution at present time, as wellas forecasting the distribution at a future time. Planning a temperaturedistribution may refer to setting or changing parameters determining theprocess of heat flow in the body, such as the power of a physicallyavailable or simulated heat source, to obtain a desired temperaturedistribution in the body. Planning a temperature distribution may alsorefer to simulating a heat transfer into the body to arrange or prepareparameters determining the process of heat flow in the body for asubsequent process such as a surgical process.

The method comprises the steps of obtaining a model of the body,simulating an application of heat to at least a part of the body anddetermining the temperature distribution in at least a part of the body.

The model of the body obtained in the initial step is related to ordirected to or describing a temperature transport mechanism ortemperature distribution in the body. The model may basically comprise a2D and/or 3D signal distribution in the body related to a physicalfeature of the body, such as perfusion or blood flow or agentconcentration or diffusion coefficients. A signal value at a point inspace and a time complies with a corresponding value of the physicalfeature of the body at the specified point and time.

Simulating an application of heat may refer to simulating at theboundary of a simulation space including at least a part of the body aboundary condition for the heat distribution such as a heat source or aheat distribution at the boundary of the simulation space. Simulating anapplication of heat may additionally refer to simulating the heatpropagation inside the simulation space. The simulation space maycomprise for example the whole body or the body plus a part of the bodyenvironment or only a part of the body including a targeted tissue or apart of the body without the targeted tissue or only the targetedtissue. The targeted tissue may be a tumour or a simulated tumour or atissue affected by another disease.

Simulating an application of heat may comprise simulating heat from asimulated heat source such as an electromagnetic field or any other heattransport carrier to the body. The simulated heat application may be forexample focal ultrasound, laser beam, catheter, x-ray, infrared,microwaves, gamma radiation, or any other radiation with a wave lengthsuitable to apply thermal energy to tissue, nano particles, colloids, orliposome.

In so doing, applying heat to the body can refer to an application ofheat which is not physically performed, but simulated.

Determining the temperature distribution in the body may refer todetermining and/or predicting the temperature or heat distribution in atleast a part of the body using the model of the body, preferably bytaking into account the physical or simulated heat source.Advantageously, the information on the physical or expected temperaturedistribution can facilitate a treatment planning where thermalvariations in tissue are expected, for example in radiotherapy, toredefine and/or control the heat monitoring set-up.

In an embodiment, determining and/or predicting the temperature or heatdistribution in at least a part of the body may comprise performingthermodynamic simulations to simulate the heat propagation and/ordistribution in the body. For this purpose a thermodynamic frameworksuch as a computer aided design system for thermodynamic simulations canbe provided being able to simulate the heat propagation and/ordistribution in the body. The thermodynamic framework is a computerprogram able to perform heat flow simulations in a simulated, preferablydiscretized, body or tissue worked up to be processed in thethermodynamic framework.

For enabling the simulation of an application and/or propagation of heatto at least a part of the body, the body model is supposed to be enteredinto the thermodynamic framework. Entering the model including ageometrical structure of the body as well as other input data such asboundary conditions and tissue parameters into the framework may enablethe program or framework to simulate a heat flow in the body similar toa real heat flow.

In an optional embodiment, a series of one or more images or imagingsequences of the body under the application of heat such as anelectromagnetic field or any other heat transport carrier can beobtained. The images can also be obtained without the application ofheat, thus describing an initial state of the body before applying heatto the body.

The images of a series may be obtained at subsequent, preferablyequidistant, time steps, thus perceiving or generating a time dependencyof the tissue parameters or heat distribution in the body. When dealingwith 2D images, the series of images shows the time dependency of 2Dtissue parameters or heat distribution in a plane cutting the body.

An imaging sequence of the body may refer to several 2D images inparallel, preferably equidistant, planes cutting the body basicallysimultaneously to obtain a 3D image of the body. Consequently, theimages of a series of imaging sequences may refer to a time dependencyof the 3D tissue parameters or heat distribution in the body.

Determining the temperature or heat distribution in at least a part ofthe body may also comprise adding the series of images or imagingsequences to the model of the body. Adding an image to the model mayrefer to obtaining from a signal distribution of an image, representinga physical feature of the body such as a concentration of contrast agentin blood, a signal distribution representing another physical feature ofthe body such perfusion. Thus, the model of the body may comprise a dataset representing 2D and/or 3D time dependent data, for example perfusiondistributions, of the body. Feeding the model into the thermodynamicframework of the body enables the calculation of the heat and/ortemperature distribution in the body. The model can be amended at anytime by adding supplementary data to the model, thus enabling to takeinto consideration new information such as a thermoablation or asurgical intervention on the targeted tissue

According to an aspect of the invention, a method of controlling ormonitoring a temperature distribution in a body is suggested. The bodycan be the whole physical body of a patient or animal, or a part of thebody such as an organ, for example liver, knee or brain, a or a lump ofbiological, human or animal, preferably living, tissue,

Controlling the temperature distribution in the body may be valuablewith a process of heat treatment of the body, especially thermalablation therapy. Such a therapy may be applied to effect localoverheating of a preferably deep-seated human tumour for destructing thetumour, to cure a cardiac arrhythmia such as supraventriculartachycardia or Wolff-Parkinson-White, to treat a coronary heart disease,to eliminate marrow cells in preparation for a bone marrow transplant,or to treat neurological disorders, for example Parkinson's disease.

Controlling the temperature distribution in the body may consequentlyrefer to setting up the parameters of a heat source applying heat to thebody so that a defined or desired spatial distribution or temporalprogression of heat in the body is obtained. With tumour ablation ornekrosis for example the desired temperature distribution can be as faras possible at least 80 degrees Celsius inside the tumour and less than41 degrees outside the tumour.

Monitoring the temperature distribution may refer to watching and/orsurveying and/or forecasting the temperature distribution in the bodywith the scope of estimating whether the current and/or forecastedtemperature distribution in the body corresponds to the defined ordesired temperature distribution.

The method comprises the steps of obtaining a model of the body,applying heat to the body and determining the temperature distributionin the body.

Obtaining a model of the body may concern a model related to or directedto or describing a temperature transport mechanism or temperaturedistribution in the body. The model may basically comprise a 2D and/or3D signal distribution in the body related to a physical feature of thebody, such as perfusion or blood flow or agent concentration ordiffusion coefficients. A signal value at a point in space and a timecomplies with a corresponding value of the physical feature of the bodyat the specified point and time. The temperature or heat distribution inthe body may correlate with the distribution of the physical feature ofthe body, so that a signal distribution in the body may correlate withthe temperature or heat distribution in the body. The model comprisesdata which is not influenced by any application of heat.

Applying heat to the body may refer to bringing a heat source to or inthe vicinity of the body so that the heat may reach or penetrate thebody. The heat source can be the source of an electromagnetic field orany other heat transport carrier. Such a heat transport carrier may befor example focal ultrasound, laser beam, catheter, x-ray, infrared,microwaves, gamma radiation, or any other radiation with a wave lengthsuitable to apply thermal energy to tissue, nano particles, colloids, orliposome.

The application of heat to the body may concern the whole body or thebody plus a part of the body environment or only a part of the bodyincluding a targeted tissue or a part of the body without the targetedtissue or only the targeted tissue. The targeted tissue may be a tumouror a simulated tumour or a tissue affected by any other disease.

From the parameters of the heat source, a thermal boundary conditionrelated to the body can be obtained, for example the heat and/ortemperature distribution at the boundary of a tissue underconsideration, for example the outer skin of the body or part of thebody such as an organ. If optionally the heat source transmits heat so,that the heat is supposed to focus in the targeted tissue, for examplein the volume of a tumour, then the heat distribution on the tissueunder consideration permits an appropriate calculation of the heatdistribution using the thermodynamic simulation framework. Reference ismade to L. Zhu and C. Diao.—Pilot point temperature regulation forthermal lesion control during ultrasound thermal therapy. Med. Biol.Eng.—.Compt., 2001, 39, 681-687 [10] which is included by reference fordetails of calculating the heat distribution inside brain tissueaccounting for an arbitrary heat source. Relevant physical parameterslike specific heat capacity of each point in space can be determined byMRI (e.g. presence of water as prominent factor to modify the specificheat capacity). For example, in paper [11] the authors describe thecalculation of the electrical conductivity in brain tissue with MRItechniques. It exists a direct relation between electrical and thermalconductivity which is well known (see Wiedmann-Franz Law). Furtherparameters may be determined by the use of a reference body. Asparameters may vary in different types of tissue, those types of tissuemay be segmented and clustered in the MR images to relate those clustersto values determined by using reference bodies. To account for heattransfer, blood volume and blood flow derived from perfusion imaging canbe incorporated. The directional heat transport through a voxel can bedetermined by the (averaged) thermal conductivity value, the dimensionsof the voxel and ΔT. [10] L. Zhu and C. Diao.—Pilot point temperatureregulation for thermal lesion control during ultrasound thermal therapy.Med. Biol. Eng. Compt., 2001, 39, 681-687[11] David S. Tuch, Van J.Wedeen, Anders M. Dale, John S. George, and John W.Belliveau—Conductivity tensor mapping of the human brain using diffusiontensor MRI. PNAS u Sep. 25, 2001 u vol. 98 u no. 20 u 11697-11701

Determining the temperature distribution in the body may refer todetermining and/or predicting the temperature or heat distribution inthe body using the model of the body and the thermal boundary conditionwhich takes into account the heat source. Advantageously, theinformation on the current or forecasted temperature distribution canfacilitate a treatment planning where thermal variations in tissue areexpected, for example in radiotherapy, to redefine and/or control theheat monitoring set-up.

In a preferable embodiment, a dose of contrast agent or tracer such asgadolinium, flavones acetic or 5,6-dimethylxantenone-4-acetic acid orany perfluorocarbon or derivative thereof can be fed into the body. Thecontrast agent can be administered for example orally or as a bolusintravenous injection. Feeding the contrast agent is particularlyadvantageous with a magnetic resonance technique focused on imaging theblood perfusion in the body.

The characterization of tumor vasculature with magnetic resonance (MR)contrast agents can use a low-molecular-weight paramagnetic gadolinium(III) chelate that extravasates in the absence of a blood-brain barrier,but cannot permeate viable cell membranes. Such a contrast agent altersthe MR signal due to his effect on the relaxation processes of tissuewater protons. The unpaired elections in this contrast agent provide anefficient mechanism for spin-lattice relaxation of water protons whenthe water molecule binds in the first or second coordination sphere ofthe contrast agent complex. As a consequence, the spin-latticerelaxation rate R₁, which is the reciprocal of the first-order timeconstant for spin-lattice relaxation T₁, is decreased in proportion tothe contrast agent concentration. The decreased R₁ leads to an increasein MRI signal intensity.

In an optional embodiment, one or more temperature probes can beattached to a specific part of the body to measure or obtain theabsolute temperature of that part of the body. Such a probe can beplaced onto the body, for example on the skin of a patient. The probecan also be placed into or inside of the body, for example by means of acatheter. The measured temperatore can be regarded as a referencetemperature and can be used to calibrate a temperature distributionobtained from the model of the body.

In an embodiment, obtaining a model of the body can comprise obtaining aseries of one or more images or imaging sequences of the body preferablyenabling the calculation of perfucion and/or diffusion properties of thebody. The series showing images obtained at subsequent time steps canenable the model to show dynamic processes such as a spin-latticerelaxation of water protons, which is typical to magnetic resonanceimaging (MRI). At the dynamic contrast enhanced (DCE) MRI, for example,the signal distribution of the images may lead to a perfusiondistribution of the body.

In an embodiment, a perfusion model of the body obtained with MRI,preferably with DCE-MRI, can be used as the model of the body. DCE-MRIinvolves acquisition of a series of T₁-weighted images before, during,and after feeding of the contrast agent. The change in signal over timemeasured by DCE-MRI reflects the exchange of contrast agent betweenvascular space and, since the contrast agent does not penetrate viablecells, extravascular-extracellular space. A blood perfusion value at apoint in space and time inside the body can be obtained from a pixelvalue of an image at that point in space and time, the pixel valuerepresenting preferably a blood plasma contrast agent concentration atthat point in space and time.

The exchange depends upon the capillary blood flow or perfusion (F),initial extraction ratio

(E), which is an index characterizing the tissue, Hematocrit (H_(ct)),contrast agent distribution volume, which is commonly assumed to equalthe fractional volume (V_(c)) of extravascular-extracellular space(EES), contrast agent concentration in tissue (C_(t)) as a function oftime (t), contrast agent concentration in blood plasma (C_(p)), andtransfer constant K^(trans). The contrast agent concentration in tissuecan thus be written as:

$\begin{matrix}{{\frac{C_{t}}{t} = {{{EF}\left( {1 - H_{ct}} \right)}\left( {C_{p} - \frac{C_{t}}{V_{e}}} \right)}}{or}} & (1) \\{{C_{t}(t)} = {{F\left( {1 - H_{ct}} \right)}{\int{{C_{p}(\tau)}^{- {k_{ep}{({t - \tau})}}}{\tau}}}}} & (2)\end{matrix}$

whereas K^(trans)=F(1−H_(ct)). Equation (1) is part of a mixed flowpermeability-limited model and equation (2) is part of a generalizedkinetic model (Toffs. et al. [1]). Other formulations of the contrastagent concentration, depending on the known tissue parameters and theboundary conditions, are according to [1] also possible. [1] Paul S.Toils, Gunnar Brix, David L. Buckley, Jeffrey L. Evelhoch, ElizabethHenderson, Michael V. Knopp, Henrik B. W. Larsson, Ting-Yim Lee, Nina A.Mayr, Geoffrey J. M. Parker, Ruediger E. Port, June Taylor, and RobertM. Weisskoff—Estimating Kinetic Parameters From DynamicContrast-Enhanced T1-Weighted MRI of a Diffusable Tracer: StandardizedQuantities and Symbols, JOURNAL OF MAGNETIC RESONANCE IMAGING 10:223-232(1999)

Alternatively, a perfusion model of the body obtained with delayedcontrast enhanced MRI or with magnetic resonance spectroscopy, can beused as the model of the body.

In another embodiment, a perfusion model of the body obtained withcomputer or x ray tomography can be used as the model of the body.Analogously to classical x ray imaging, the computer tomography is basedon the weakening of x rays while passing through the examined tissue.The measurements of radiation attenuation caused by the tissue arerecorded in a large number of projections. In addition to the purelyanatomical information, reference on the blood perfusion can be alsoobtained. To this end a time sequence of images of the consideredanatomical region is obtained. If during such a dynamic investigation acontrast agent is fed to the body, it is possible to obtain the time andspace dependent distribution of the perfusion in the tissue(habilitation treatise [2]) [2] Hans-Jörg Wittsack—Ermittlung vonPerfusionsparametern anhand dynamischer, kontrastmittelgestützterSchnittbildverfahren, Habilitationsschrift, Düsseldorf 2007

In an embodiment, a model based on diffusion coefficients obtained withmagnetic resonance imaging can be used as the model of the body. Forthis purpose the temperature dependence of the translationalself-diffusion coefficient and viscosity are established on the basis ofthe Stokes-Einstein relationship (Simpson, Carr [1]). When an object issubjected to changing temperatures, these temperature changes inducechanges in the diffusion coefficient which can be calculated fromdifferentiating the Stokes-Einstein equation as long as the variationsof the activation energy with the temperature are small.

The effect of molecular diffusion in the presence of a magnetic fieldgradient on MR spin-echo signals is well known. Diffusion produces apure amplitude attenuation of the MR signal due to the loss of phasecoherence between processing spins produced by their random walk throughthe gradient. This amplitude attenuation depends only on the diffusioncoefficient D and the gradient. Thus it is possible to obtain theself-diffusion coefficient with MR1 measurements, from which thetemperature distribution can be obtained.

In an embodiment, a model based on proton-frequency-shift alterationsobtained with magnetic resonance imaging can be used as the model of thebody. With the PRF-shift method of thermometry, the phase-shiftsensitivity or a thermal coefficient is generally modeled as being afunction of the gyromagnetic ratio for H nuclei, the magnetic fieldstrength and the apparent PRF-thermal coefficient containingcontributions from changes in the electron screening constain andmagnetic susceptibility. In a conductive material, a transmittedmagnetic field will undergo amplitude attenuation and phase retardation,giving rise to a variation in tip angles and phase over the body. Inparticular, the spatial nature of the phase variation in the MR imagewill depend on the material properties and the imaging coil(s) used totransmit and receive the RF signal. Temperature induced changes in thematerial's electrical conductivity and, to a lesser extent, permittivitywill result in changes in the wave number of the RF wave and, thus, thephase-retardation of the magnetic field (see [4], [5], [6], [7]). [4] Y.Ishihara, et al. SMRM Proc. 4803 (1992)[5] J. C. Hindman J. Chem. Phys.44(12):4582-4592 (1966)[6] J. Depoorter MRM 34:359-367 (1995)[7] P.Bottomley, et al. Phys. Med. BioZ. 23(4):630-643 (1978)

In another embodiment, a reference model directed to a transportmechanism or reference temperature distribution in a reference body canbe obtained from a data base. The reference body has well known tissueparameters and distributions of physical features such as perfusion ortemperature. The data of the reference body can be used to calibrate thevalues of a relative temperature distribution obtained from the model ofthe body.

In an embodiment, a set of tissue parameters can be obtained from theimages of the body under consideration. The tissue parameters can be forexample the permeability surface area product of the endothelium and/orfractional size of the extravascular extracellular space and/orhematocrit and/or total permeability of capillary wall and/orpermeability surface area product per unit mass of tissue and/or anyother tissue parameter used in the work of Tofts et. al. [1]. Any othertissue parameters related directly or indirectly to the distribution ofcontrast agent or to another physical entity correlated with the signaldistribution shown in the images of the body can be obtained from themodel of the body. The method of obtaining the tissue parameter mayconsist in establishing a system of preferably linear equations from theequations (1) or (2) or from similar equations determining arelationship between the measured signals of the images and the physicalfeature correlated with the signals. The procedure may consist in a)applying for example equation (1) to several contrast agentconcentrations correlated with corresponding signal pixels of a image,b) combining the obtained equations to a system of over-determinedlinear equation having the tissue parameters as unknowns, and e) solvingfor the unknowns by an optimization method such as a least squaresmethod.

In another embodiment, an individualized model directed to a temperaturetransport mechanism or temperature distribution mechanism in the bodyunder consideration can be obtained from the reference model and thetissue parameters. If for example the geometry of the reference body issimilar to that of the body under consideration, then a 3D rigid and/ornon-rigid registration of the reference model to the model underconsideration can be performed. Subsequently, the distribution of thephysical feature, for example perfusion, of the reference model, can beadapted to the model under consideration by taking into considerationthe differences between the tissue parameters of the body underconsideration and the reference body.

With a perfusion model as the model of the body, a perfusiondistribution of the body composing the perfusion model can initially beobtained from a signal distribution of the images by applying theframework of Tofts et. al. [1] expressed for example by the equations(1) or (2).

Subsequently, the temperature at a point in space and time can bedetermined from the perfusion at that point in space and time. Toachieve this, a tabular dependency of temperature in space and time fromthe blood perfusion at that point in space and time can be used. Aswell, a tabular dependency of a temperature gradient or a time dependentchange of the temperature at a point from the blood perfusion at thatpoint can be used. Since the reference body has well known tissueparameters and distributions of physical features such as perfusion ortemperature, the value pairs perfusion/temperature, orperfusion/temperature gradient, or perfusion/time dependent change ofthe temperature, can be obtained from the reference body. The referencetables obtained this way can be stored in the data base.

If a temperature value is required which is not comprised in thereference table, numerical interpolation with piecewise linear ornonlinear functions, e.g. cubic splines, or extrapolation, can be used.

Preferably, obtaining the temperature at a point in space and time fromthe perfusion at that point in space and time can be performed using abioheat equation such as the Pennes equation. This relation is based onthe fact, that heat transfer at any given point in the tissue isdirectly proportional to the local temperature gradient. Taking intoconsideration the time dependency of the heat transfer, the energybalance for a considered body can be written as:

$\begin{matrix}{\frac{\partial T}{\partial t} = {\frac{1}{\rho \; c_{v}}\left\lbrack {{k_{T}{\nabla^{2}T}} - {C\left( {T - T_{b}} \right)}} \right\rbrack}} & (3)\end{matrix}$

The equation (3) is known as bioheat equation. Where K is the thermalconductivity, rho is the blood density, Cv is the specific heat of bloodand C the local blood perfusion rate (called F in equation (1)). Seepaper [10] for a detailed description of the utility of this equationthat explains the temperature distribution in brain tissue. Additionalterms in the right-hand side can appear depending on different heatsources (like external radiation field, etc). The dependency of thetemperature from a signal distribution obtained from images or from themodel of the body can be determined according to the following sequence:a) obtaining a perfusion distribution as well as the tissue parametersof the body from the signal distribution using one of the equations (1)or (2) or a similar equation, b) obtaining the temperature or heatdistribution in the body from the perfusion distribution and tissueparameters using the equation (3). Note that according to Tuch et al.(reference [11]) the thermal conductivity can also be obtained by MRItechniques.

Preferably, obtaining one or more images or imaging sequences of thebody can refer to applying an imaging method such as magnetic resonance,computer tomography, X-rays, or fluoroscopic imaging, to the body. Theimages obtained this way may refer to a state of the body before orduring a therapy such as a thermal or chemo therapy, the body comprisingtissue that needs to be observed such as a tumour.

Optionally, one or more images or imaging sequences of the body can beretrieved from the data base. These images may refer to a differentstate of the body, in which for example the body does not comprise thetumour.

In an optional embodiment, the relation between thermal and perfusiondistribution inside the body is based on the thermodynamic energybalance embodied in the Pennes bioheat equation. The bioheat equationwith appropriate boundary conditions yields the temperature distributionthroughout the at least part of the body under consideration. Obtainingthe thermal distribution can comprise, although it is not required, thesteps of determining an initial perfusion distribution of the bodybefore applying heat to the body, calculating a temperature distributionin the body based on the initial perfusion distribution and a heat powerinput upon commencement of the heat application, and iterativelyadjusting the perfusion distribution of the body based on the calculatedtemperature distribution and recalculating the temperature distributionbased on the adjusted perfusion distribution and the heat power.

The thermal calculation can be performed by a finite-difference method.The calculation region is divided into finite-sized sub-volumes oftissue that are taken to be sufficiently small so as to convert thedifferential expressions in the energy balance to algebraic expressionswith an sufficient degree of approximation. An algebraic equation isthus obtained for each sub-volume of tissue. Simultaneous solution ofthese algebraic equations by standard linear algebra techniques yieldsthe temperature at the center of each tissue sub-volume, which providesan approximation of the true, continuous temperature distribution in thetissue.

The time dependent variations of temperature in the body is tracked bysubdividing time into short, discrete intervals or time steps, such asone second intervals in an exemplary embodiment. The numerical frameworkfor the calculation complies with the state of the art methods common tothermodynamic simulations.

An initial condition or initial perfusion distribution of the body ortargeted tissue can be determined in the first instance with DTE-MRI.This initial condition includes an initial perfusion rate distributionin the body. The initial perfusion distribution, along with a heat powerinput can be fed into the thermodynamic simulation framework to solvethe bioheat equation to yield a temperature distribution in the body.The temperature of tissue in the body is utilized to adjust the tissueparameters of the body, since the tissue parameters are highly dependenton temperature. The relationship of the tissue parameters andtemperature is based on in-vitro experimental measurements that areknown in the art.

The rate of blood perfusion in the targeted tissue can be dependent ontemperature, time of exposure to elevated temperatures, and the locationof the targeted tissue within the body. In turn, the rate of bloodperfusion affects the temperature elevation of tissue in response tocontinued exposure to heat. Therefore, in order to accurately model thetemperature distribution in the body, the rate of blood perfusion mustbe continually updated for each iterative solution of the bioheatequation. Therefore, a perfusion adjustment is determined, based on thetemperature and location of the targeted tissue, to adjust the perfusionrate input to the mathematical model.

In an embodiment, the calculation of the temperature distribution canused for determining a volume of necrosis in the targeted tissue basedon the time and temperature relationship therein. The determination ofthe volume of necrosis, which can be defined as a destruction of apredetermined percentage, is also important to signify to a treatingphysician when therapy is complete and may be discontinued. Byaccurately modeling temperature and the extent of necrosis during atreatment session, the total session time can be minimized for eachpatient, which is highly desirable to optimize the thermal dosagereceived by the patient.

Calculation of the fraction of cells that have been destroyed requiresknowledge of the chemical kinetic rate constant for the damage mechanismof cells in the targeted tissue, which varies strongly with temperature.The rate constant and its variation with temperature are established bycomparing the predictions of the thermal model against experimentallymeasured temperatures in a number of patients during a thermal therapyprocedure. Specifically, the rate constant can be determined using anArrhenius rate constant model [9]. [9] Perez and Brady's principles andpractice of radiation oncology, Wolters Kluwer Health, 2007

Preferably, the perfusion distribution of the body can be adjusted basedon the determined volume of necrosis. The determination of a volume ofnecrosis may signify to a treating physician when therapy is completeand may be discontinued.

In an embodiment, the images or imaging sequences can be obtained withmagnetic resonance T1-weighted gradient-echo sequences or with magneticresonance proton-frequency-shift alterations or with x ray tomography.

In another embodiment, absolute temperature values of the body can beobtained by relating one or more reference temperature values obtainedfrom measurements and/or from the data base to corresponding one or moretemperature values of the temperature model of the body. The temperaturevalues of the body in the data base can also rely on measurements.

In an embodiment, the calculated and/or forecasted temperaturedistribution within the body, especially in the targeted tissue, can bedisplayed and/or monitored. Displaying such information can be useful tosignify to a treating physician when therapy is complete and has to besuspended or interrupted. For the display, a temperature map can beused.

The invention also relates to a computer program, which, when loaded orrunning on a computer, performs or supports the method or steps as setforth above. Furthermore, the invention relates to a program storagemedium or a computer program product comprising such a program.

According to a further aspect, the invention relates to an apparatus orsystem for predicting or planning a temperature distribution in a bodyusing a model of the body. The system comprises a imaging equipmentsuitable to obtain images of at least a part of the body, a data baseconnected to the imaging equipment suitable to store the model of thebody and to retrieve the stored information and a data processing unitconnected to the imaging equipment and/or to the data base. The dataprocessing unit is capable to obtain the model directed to a temperaturetransport mechanism or temperature distribution in the body.

In an embodiment, the data processing unit can be suitable to simulatean application of heat to at least a part of the body.

In another embodiment, the system can comprise a heat source such as asource of an electromagnetic field or any other heat transport carrier,for example focal ultrasound, laser beam, catheter, x-ray, infrared,microwaves, gamma radiation, or any other radiation with a wave lengthsuitable to apply thermal energy to tissue, nano particles, colloids, orliposome.

In an embodiment, the imaging equipment can be suitable to obtainingimages or imaging sequences with magnetic resonance Ti-weightedgradient-echo sequences or with magnetic resonanceproton-frequency-shift alterations or with magnetic resonance tomographyor with x-ray tomography.

The data processing unit can be suitable to determine and/or predict thetemperature or heat distribution in at least a part of the body usingthe model of the body.

In an embodiment, the model of the body can be a perfusion model of thebody obtained with magnetic resonance imaging or computer tomography, ora model based on diffusion coefficients or proton-frequency-shiftalterations, both being obtained with magnetic resonance imaging.

In another embodiment, the data base is suitable to store tissueparameters of the body and/or a reference perfusion model of a referencebody and/or a reference temperature model of a reference body.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate several embodiments of theinvention and together with the description, serve to explain theprinciples of the invention.

FIG. 1 illustrates a process of predicting or planning a temperaturedistribution in a body according to a first embodiment of the presentinvention;

FIG. 2 illustrates a process of controlling or monitoring a temperaturedistribution in a body according to a second embodiment of the presentinvention;

FIG. 3 illustrates the process of predicting or planning a temperaturedistribution in a body according to a third embodiment of the presentinvention; and

FIG. 4 illustrates the process of controlling or monitoring atemperature distribution in a body according to a fourth embodiment ofthe present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Reference will now be made in detail to the exemplary embodiments of theinvention illustrated in the accompanying drawings.

In the embodiment illustrated in FIG. 1, the invention relates to aprocess of predicting or planning a temperature distribution 52 in abiologic tissue such as a body. The process comprises the steps ofobtaining a model of the body 50 (S12), simulating an application ofheat (S18) to the body (S16) and determining the temperaturedistribution 52 in the body (S16).

The model of the body 50 obtained in the initial step is related to ordirected to a temperature distribution 52 in the body. The modelcomprises a 2D and/or 3D signal distribution in the body related toperfusion of the body. The model is obtained either from DTE-MRI imagesdelivered by an imaging equipment 12, or from a data base 10.

Simulating an application of heat (S14) refers to simulating at theboundary of a simulation space including at least a part of the bodysuch as the head, knee or another organ of a patient, a boundarycondition for the heat distribution at the boundary of the simulationspace. Simulating the application of heat additionally refers tosimulating the heat propagation inside the simulation space. Thetargeted tissue usually is a tumour.

Determining the temperature distribution 52 in the body (S16) refers todetermining and predicting the temperature or heat distribution in thebody using the model of the body 50 by taking into account the simulatedheat source. Simulating the application of heat (S14) requires athermodynamic framework 18 such as a computer aided design system forthermodynamic simulations to simulate the heat propagation and/ordistribution in the body.

In this embodiment, the heat is not physically applied to the body.Instead, as already mentioned, the application of heat is simulated.

In the embodiment illustrated in FIG. 2, the invention relates to aprocess of controlling or monitoring a temperature distribution 52 in abody. The body usually is part of the body such as an organ, for exampleliver, knee or brain of a patient.

Controlling the temperature distribution 52 in the body refers tosetting up the parameters of the heat source 24 applying heat to thebody so that a defined or desired spatial distribution or temporalprogression of heat in the body is obtained. With tumour ablation orhyperthermia of a tumour the desired temperature distribution 52 is asfar as possible at least 80 degrees Celsius inside the tumour and lessthan 41 degrees outside the tumour.

The process comprises the steps of obtaining a model of the body 50(S12), applying heat to the body (S18), and determining the temperaturedistribution 52 in the body (S16).

Applying heat to the body (S18) refers to bringing the heat source 24 toor in the vicinity of the body so that the heat may reach or penetratethe body. The heat source 24 is a microwave source. The heat sourcegenerates at the boundary of a simulation space including at least apart of the body such as the head, knee or another organ of a patient, aboundary condition for the heat distribution at the boundary of thesimulation space. The propagation and distribution of heat is obtainedin the embodiment similarly to the embodiment exemplified in FIG. 1.

The step of obtaining a model of the body 50 (S12) concerns a perfusionmodel. The perfusion model is obtained from DTE-MRI images delivered bythe medical imaging equipment 12 or obtained from the database 10.

Determining the temperature distribution 52 in the body (S16) refers todetermining and/or predicting the temperature or heat distribution inthe body using the model of the body 50 by taking into account the heatdistribution at the boundary of the simulation space generated by theheat source 24.

In the embodiment shown in FIG. 2, the heat is physically applied to thebody. But above this physical application of heat, the process ofcalculating the heat propagation and distribution in the body based onthe heat distribution at the boundary of the simulation spacecorresponds to the process shown in FIG. 1.

In the embodiment illustrated in FIG. 3, the invention relates to aprocess of predicting or planning a temperature distribution 52 in abiologic tissue such as a body. This embodiment is similar to that shownin FIG. 1.

The initial step consists in feeding a contrast agent or tracer (S10)such as gadolinium (III) into the body. This step supports the procedureof obtaining DTE-MRI images from a patient, whereat the contrast agentis supposed to improve the imaging of blood perfusion in the body of thepatient.

The step of obtaining the model of the body 50 (S12) comprises theapplication of a frame-work establishing a relation between the signaldistributions in images obtained with a DIE-MRI imaging equipment 12 andthe perfusion distribution in the body. Such a perfusion framework 14 isbased on equations (1) or (2) or on similar equations establishing therelation between a signal distribution of a 2D or 3D image and aperfusion distribution.

The step of determining the temperature distribution 52 (S16) from theperfusion distribution of the body comprises the application of aframework establishing a relation between the perfusion distribution andthe temperature distribution 52 in the body. Such a framework is basedon a bioheat framework 20 such as equation (3). The dependency of thetemperature from a signal distribution obtained from images or from themodel of the body 50 is determined after obtaining a perfusiondistribution as well as the tissue parameters of the body from thesignal distribution shown in the DTE-MRI images.

In the embodiment illustrated in FIG. 4, the invention relates to aprocess of controlling or monitoring a temperature distribution 52 in abiologic tissue such as a body. This embodiment is based on that shownin FIG. 2 and is similar to that shown in FIG. 4. The embodiment shownin FIG. 4 differs from that shown in FIG. 3 in the way of treating theapplication of het to the body: In one embodiment (FIG. 3), theapplication of heat is simulated, in the other (FIG. 4), the applicationof heat is physically performed.

Predicting and displaying temperature gradients in tissue together withinformation of the biological process triggered by any heat source 24 isimplemented in a device and it is based on patient-specific information,heat source properties for example focal ultrasound, laser beam,catheter, x-ray, infrared, microwaves, gamma radiation, or any otherradiation with a wave length suitable to apply thermal energy to tissue,nano particles, colloids, liposome. The application of heat (S18) isperformed by electromagnetic fields and others heat transport carriersas well as any administrated agent supporting the heat transfer. Inaddition, the method also takes into account physiological tissueproperties like heat capacity, vascular permeability, hydraulicconductivity, pore fraction and diffusivity. As embodiment the methodpredicts temperature and effects not only before and during treatment orheat transfer but also after its interruption.

An embodiment of the invention consists of the display of exposure time,necrotic tissue density, swelling degree, tumor size and othersphysiological or physical properties that can lead to modification orinterruption of the treatment.

The invention is very useful to support treatment planning where thermalvariations in tissue are expected (e.g. radiotherapy) to prevent andcontrol side effects caused by an increase in temperature of tissue aswell as to redefine and/or control automatically and in-situ the heatmonitoring set-up. Such a monitoring of the temperature can facilitatemany clinical procedures where a certain level of temperature has to bekept for a certain period of time, like ultrasound hyperthermia or localstimulation of the immune system and many more.

Any kind of heat source 24 like ultrasound, heat transport particles andother energy carriers can be used. The calculation of temperature is notsolely based on perfusion but also on patient-specific information (age,sex) and properties like calorific capacity, diffusivity and otherphysiological and physical properties. Perfusion variations as well asother physiological properties are directly obtained by DCE-MRI and/orCT-Perfusion techniques during treatment.

Temperature profiles are obtained by the so-called perfusion techniques(DCE-MRI and/or CT-Perfusion). Also additional information can be insitu extracted regarding physiological properties of the tissue (e.g.necrosis, swelling), so it is possible to relate the temperature changewith the underlying biological process. This allows tracking the effectsthat the heat transport entity has on tissue so one would be able toregulate and control in situ the heat source 24 according to thisinformation.

Any administrated agent or combination supporting or affecting the heattransfer can be applied and agent specific information is processed topredict and display temperature gradients in tissue.

Physiological, metabolic, chemical and physical tissue properties likeheat capacity, vascular permeability, hydraulic conductivity, porefraction and diffusivity are processed to predict and displaytemperature gradients in tissue.

The information about the temperature gradients and its effects intissue is used for treatment planning purposes, treatment controllingpurposes, treatment follow up purposes, diagnostic purposes

LIST OF REFERENCE SIGNS

10 data base

12 medical imaging equipment

14 perfusion framework

16 data processing unit

18 thermodynamic framework

20 bioheat framework

22 bolus

24 heat source

50 model of the body

52 temperature distribution of the body

S10 simulating a distribution of tracer in the body

S12 obtaining a model of the body

S14 simulating an application of heat to the body

S16 determining the temperature distribution in the body

S18 applying heat to the body

REFERENCES

[3] Simpson, J. H. and Carr H. Y., Phys. Rev. 111:1401 (1958)

[8] E. A. Adebile, B. N. Akintewe, J. K. Ogonmoyela—TemperatureVariations in Bilolgical Tissues Due to Spatial Dependent BloodPerfusion during Microwave Heating, J. Engineering and Applied Sciences2 (3): 509-515, 2007

1. Method of predicting or planning a temperature distribution in a body comprising the steps of: a) obtaining a model of the body related to a temperature transport mechanism or temperature distribution in the body; b) simulating an application of heat to at least a part of the body such as targeted tissue; c) determining and/or predicting the temperature or heat distribution in at least a part of the body using the model of the body.
 2. Method according to claim 1, wherein determining and/or predicting the temperature or heat distribution in at least a part of the body comprises: performing thermodynamic simulations to simulate the heat propagation and/or distribution in the body; and/or using optionally a series of one or more images or imaging sequences of the body without or under the application of heat such as an electromagnetic field or any other heat transport carrier from a heat source and adding the series of images or imaging sequences to the model of the body.
 3. Method of controlling or monitoring a temperature distribution in a body comprising the steps of: d) obtaining or providing a model of the body related to a temperature transport mechanism or temperature distribution in the body; e) applying heat to at least a part of the body such as targeted tissue; f) determining and/or predicting the temperature or heat distribution in the body using the model of the body.
 4. Method according to claim 1, further comprising: feeding into the body a dose of contrast agent or tracer such as Gadolinium.
 5. Method according to claim 1, wherein obtaining a model of the body comprises: obtaining a series of one or more images or imaging sequences of the body preferably enabling the calculation of perfusion and/or diffusion properties of the body; and/or obtaining a perfusion model of the body achieved by magnetic resonance imaging and/or computer tomography; and/or obtaining a model based on diffusion coefficients or proton-frequency-shift alterations, both being achieved with magnetic resonance imaging.
 6. Method according to claim 1, further comprising: obtaining from a database a reference model directed to a transport mechanism or temperature distribution mechanism in a reference body; and/or obtaining from the images of the body under consideration a set of tissue parameters describing the body or parts of the body, such as the permeability surface area product of the endothelium and/or fractional size of the extravascular extracellular space; and/or obtaining from the reference model and the tissue parameters an individualized model directed to a temperature transport mechanism or temperature distribution mechanism in the body under consideration.
 7. Method according to claim 1, wherein obtaining the temperature model from a model of the body, when using a perfusion model as the model of the body, refers to: obtaining a perfusion distribution of the body or of the model from a signal distribution of the images; using a tabular dependency of a temperature or a temperature gradient or a time dependent change of the temperature at a point in space and time from the blood perfusion at that point in space and time; and/or using a bioheat equation such as the Pennes equation.
 8. Method according to claim 1, further comprising: determining an initial perfusion distribution of the body before applying heat to the body; calculating a temperature distribution in the body based on the initial perfusion distribution and a heat power input upon commencement of the heat application; iteratively adjusting the perfusion distribution of the body based on the calculated temperature distribution and recalculating the temperature distribution based on the adjusted perfusion distribution and the heat power.
 9. Method according to claim 1, further comprising: determining a volume of necrosis in the targeted tissue based on the time and temperature relationship therein; adjusting the perfusion distribution of the body based on the determined volume of necrosis.
 10. Method according to claim 1, wherein the images or imaging sequences are obtained with magnetic resonance T1-weighted gradient-echo sequences, or with magnetic resonance proton-frequency-shift alterations or with x ray tomography.
 11. Method according to claim 1, further comprising: obtaining absolute temperature values of the body by relating one or more reference temperature values obtained from measurements or from the database to corresponding one or more temperature values of the temperature model of the body.
 12. Method according to claim 1, further comprising: displaying and/or monitoring the calculated and/or forecasted temperature distribution within the body, especially in the targeted tissue.
 13. Computer program which, when loaded or running on a computer, performs or supports the method of claim
 1. 14. Program storage medium or computer program product comprising the program of claim
 13. 15. System for predicting or planning a temperature distribution in a body using a model of the body, said system comprising: a imaging equipment suitable to obtain images of at least a part of the body, a database connected to the imaging equipment suitable to store images of the body and to retrieve the stored information, a data processing unit connected to the imaging equipment and/or to the database, the data processing unit being capable to obtain a model directed to a temperature transport mechanism or temperature distribution in the body, and/or a device suitable to perform or support the method of claim
 1. 16. System according to claim 15, wherein the data processing unit is suitable to simulate an application of heat to at least a part of the body.
 17. System according to claim 15, wherein the system comprises a heat source such as a source of an electromagnetic field or any other heat transport carrier, for example focal ultrasound, laser beam, catheter, x-ray, infrared, microwaves, gamma radiation, or any other radiation with a wave length suitable to apply thermal energy to tissue, nano particles, colloids, or liposome.
 18. System according to claim 15, wherein the data processing unit is suitable to determine and/or predict the temperature or heat distribution in at least a part of the body using the model of the body, and/or the imaging equipment is suitable to obtain images or imaging sequences with magnetic resonance T1-weighted gradient-echo sequences or with magnetic resonance proton-frequency-shift alterations or with magnetic resonance tomography or with x-ray tomography.
 19. System according to claim 15, wherein the model of the body is a perfusion model of the body obtained with nuclear magnetic resonance or computer tomography, and/or the model of the body is a model based on diffusion coefficients or proton frequency-shift alterations, both being obtained with nuclear magnetic resonance, and/or the database is suitable to store tissue parameters of the body and/or a reference perfusion model of a reference body and/or a reference temperature model of a reference body. 